• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1053-1065
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• 2019

Land use statistics calculation is very informative data as the activity data for calculating exact carbon absorption and emission in post-2020. To effective interpretation by land use category, This study classify automatically image interpretation by land use category applying forest aerial photography (FAP) to deep learning model and calculate national unit statistics. Dataset (DS) applied deep learning is divided into training dataset (training DS) and test dataset (test DS) by extracting image of FAP based national forest resource inventory permanent sample plot location. Training DS give label to image by definition of land use category and learn and verify deep learning model. When verified deep learning model, training accuracy of model is highest at epoch 1,500 with about 89%. As a result of applying the trained deep learning model to test DS, interpretation classification accuracy of image label was about 90%. When the estimating area of classification by category using sampling method and compare to national statistics, consistency also very high, so it judged that it is enough to be used for activity data of national GHG (Greenhouse Gas) inventory report of LULUCF sector in the future.

• Land and Housing Review
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• v.3 no.1
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• pp.83-88
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• 2012

In this study, physical characteristics of cement and/or concrete materials that are typically used for energy-foundation (EF) structures have been studied. The thermal conductivity and structural integrity of the cement-based materials were examined, which are commonly encountered in backfilling a vertical ground heat exchangers, cast-in-place concrete piles and concrete lining in tunnel. For this purpose the thermal conductivity and unconfined compression strength of cement-based materials with various curing conditions were experimentally estimated and compared. Hydration heat generated from massive concrete in the cast-in-place concrete energy pile was observed for 4 weeks to estimate its dissipation time in the underground. The hydration heat may mask the in-situ thermal response test (TRT) result performed in the cast-in-place concrete energy pile. It is concluded that at least two weeks are needed to dissipate the hydration heat in this case. In addition, a series of numerical analysis was performed to compare the effect of thermal property of the concrete material on the cast-in-place pile.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_2
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• pp.587-597
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• 2007

This study determines matching size for digital elevation model (DEM) production according to land cover property from IKONOS Geo-level stereo image. We applied area based matching method using correlation coefficient of pixel brightness value between the two images. After matching line (where "matching line" implies straight line that is approximated to complex non-linear epipolar geometry) is established by exterior orientation parameters to minimize search area, the matching is carried out based on this line. The experiment is performed according to land cover property, which is divided off into four areas (water, urban land, forest land and agricultural land). In each of the test areas, matching size is selected using a correlation-coefficient image and parallax image. As the results, optimum matching size of the images was selected as $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.229-233
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• 2007

This study is to test the applicability of QuickBird image for non-point source pollution assessment. SWAT (Soil and Water Assessment Tool) model was adopted and the model was calibrated for a stream watershed of 255.4 $km^2$ Landsat land use data. For model application with QuickBird image, a precise agricultural land use map of 1.16 $km^2$ area located in the upstream watershed was produced by field investigation. The model was run with the combination of land use and soil map scales (1:5,000, 1:25,000 and 1:50,000). The results were compared and analyzed for the contribution of non-point source pollution by the land use scale and contents.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.03a
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• pp.517-524
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• 2001

In this study, the effect of relative density and fine contents(Finer then # 0.08mm sieve) on liquefaction phenomenon in reclaimed land by hydraulic hammer compaction is analyzed. For more site-specific studies, reclaimed land in Inchon International Airport is selected and the cyclic triaxial tests are performed on disturbed samples. In cyclic triaxial tests, the characteristics of reclaimed land in Inchon International Airport are considered sufficiently. The liquefaction resistance stress ratio ($\tau$$\ell$/$\sigma$v') can be defined by relative density 40, 50, 60, and 70% and also by fine contents : 0, 10, 20, 30, and 40% under relative density (D$\_$r/) 50% used disturbed samples. From tile result of comparing tile cyclic triaxial tests, it is shown that the liquefaction strength of soil increases with increases of relative density and fine contents. Fspecially fine contents is the main factor affecting the liquefaction potential. In addition, the liquefaction resistance stress ratio is reduced by the increase of fine content and tile ratio of change is steep until fine contents 20% and that is flexible during the range of fine contents 20% to 40%. Through this study, it is proved that the soil characteristics (fine contents 5∼20%) of the reclaimed land in Inchon International Airport flays an important role in the reduction of liquefaction potential.

• Journal of Environmental Impact Assessment
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• v.19 no.3
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• pp.347-356
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• 2010

Forests are being seriously fragmented as a result of land development. Land development with disregard to its subsequent environmental impacts is a primary threat to biodiversity by incurring massive habitat losses and changes in structure and composition of forests. The purpose of this study was to develop the impact assessment model for quantitative distance or degree of disturbance by land developments. This study conducted a survey about structure and composition of forest species to determine degree of impact from land development. The edge effect of forest fragmentation on the number of bird species, population size, and bird diversity was obvious. In particular, the bird diversity sharply declines around the forest edge where intensive land development projects take place. To assess the disturbance of forest species, the factors selected were the bird diversity and the rate of edge species. The impact assessment model about bird diversity was explained by type of forest fragmentation and type of vegetation ($R^2$=0.23, p<0.005). The other model about edge species explained by a distance, type of forest fragmentation, type of vegetation, and width of road ($R^2$=0.34, p<0.001). In order to test the applicability of the model developed in this study, the models was applied to the Samsong housing development in Goyang-si, Gyunggi-do. The impacts of land development on the bird species were reasonably quantified to suggest effective mitigation measure. The impact assessment model developed in this study is useful to assess the magnitude of disturbance of bird species. Particularly, the model could be applied to the current Environmental Impact Assessment practices to predict and quantify the impacts of land developments projects on forest bird species.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.1
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• pp.61-69
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• 2004

A long-term growth simulation was performed at 99 land units in Yeoncheon county to test the potential adaptability of each land unit for growing soybean cultivars. The land units for soybean cultivation(CZU), each represented by a geographically referenced land patch, were selected based on land use, soil characteristics, and minimum arable land area. Monthly climatic normals for daily maximum and minimum temperature, precipitation, number of rain days and solar radiation were extracted for each CZU from digital climate models(DCM). The DCM grid cells falling within a same CZU were aggregated to make spatially explicit climatic normals relevant to the CZU. A daily weather dataset for 30 years was randomly generated from the monthly climatic normals of each CZU. Growth and development parameters of CROPGRO-soybean model suitable for 2 domestic soybean cultivars were derived from long-term field observations. Three foreign cultivars with well established parameters were also added to this study, representing maturity groups 3, 4, and 5. Each treatment was simulated with the randomly generated 30 years' daily weather data(from planting to physiological maturity) for 99 land units in Yeoncheon to simulate the growth and yield responses to the inter-annual climate variation. The same model was run with input data from the Crop Experiment Station in Suwon to obtain a 30 year normal performance of each cultivar, which was used as a "reference" for evaluation. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to evaluate the suitability of each land unit for growing a specific cultivar. A computer program(MAPSOY) was written to help utilize the results in a decision-making procedure for agrotechnology transfer. transfer.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.10a
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• pp.46-55
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• 2006

There are many kinds of braced cut wall methods as the sheet pile, SCW, CIP and slurry wall which is adoptable for a deep excavation construction in a coastal filled land. The braced cut wall which has a strong stiffness is very stable but it has the weak point that the construction cost is high. Thus when a braced cut wall is designed, the geotechnical engineers choose the braced cut wall which has more safe and economic in the consideration of surrounding buildings near the construction site. Especially, when the sheet pile method as a braced cut wall is cheesed, the layer order and consistence of a coastal deposit stratum are considered and the pile driving method is also considered. This paper introduces the case that the originally box-type sheet pile wall was changed to U-type and high strength material after the pilot test at the subway construction site in a coastal filled land. This paper also introduces the case that the sheet pile's driving method was changed to special method in the section of the temporary coffer dam which had made when the present coastal filled land was formed.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.144-147
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• 1999

The objective of this study is to quantitatively evaluate the effects of various SAR speckle reduction methods for multisource land-cover classification by backpropagation neural network, especially over the coastal region. The land-cover classification using neural network has an advantage over conventional statistical approaches in that it is distribution-free and no prior knowledge of the statistical distributions of the classes is needed. The goal of multisource land-cover classification acquired by different sensors is to reduce the classification error, and consequently SAR can be utilized an complementary tool to optical sensors. SAR speckle is, however, an serious limiting factor when it is exploited for land-cover classification. In order to reduce this problem. we test various speckle methods including Frost, Median, Kuan and EPOS. Interpreting the weights about training pixel samples, the “Importance Value” of each SAR images that reduced speckle can be estimated based on its contribution to the classification. In this study, the “Importance Value” is used as a criterion of the effectiveness.

• Spatial Information Research
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• v.5 no.2
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• pp.177-183
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• 1997

S1he concept of a class in the land-use classification system can be equally applied to a class in the land-use-change classification. The maximum likelihood method using linear discriminant function and Markov transition matrix method were integrated to a synthetic modeling effort in order to project spatial allocation of land-use-change and quantitative assignment of that prediction as a whole. The algorithm of both the multivariate discriminant function and the Markov chain matrix were discussed and the test of synthetic model on the study area was resulted in the projection of '90 year as well as '95 year land -use classification. The accuracy and the issue of modeling improvement were discussed eventually.